SLAM technology makes real smart robots no longer far away from us

There was a robot , which was locked into an empty room filled with miscellaneous things. The robot is very scared because he has never been here before, and he doesn't know it at all. There are three main problems that make him feel scared:

1. Where are you?

2. What is this place?

3. How to get out of this place?

In the theory of SLAM (Simultaneous Localization And Mapping), the first problem is called Localization, the second is called Mapping, and the third is the subsequent path planning (Navigation). ).

Simply put, SLAM refers to the robot's own sensor to obtain the perceptual information in the unknown environment, incrementally create a map of the surrounding environment, and use the created map to achieve autonomous positioning.

In fact, the positioning of maps and the creation of maps with positioning are easy to solve, but the maps without maps and unresolved maps create the same problem as “chickens and chickens” (the perfect positioning requires a Unbiased maps, but such maps require precise location estimates to depict), no way to start.

The sensors installed inside the robot (including the odometer, compass, accelerometer, etc.), because there is no reference to external information, the accumulation of errors after a long walk is relatively large, and the practicality is poor. Therefore, relying on internal sensors, while sensing the environment with external sensors (such as vision sensors, laser radar, etc.), can help robots solve this problem.

A robot developed by the Darmstadt University of Technology in Germany is using laser imaging detection and ranging technology to map the maze

The map depicted by the robot above

At present, the implementation of SLAM technology mainly includes VSLAM, Wifi-SLAM and Lidar SLAM.

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